The Impact of Anxiety and Depression on the Quality of Life of Hemodialysis Patients
Bibliographic record
Abstract
PURPOSE: This study was to explore the impact of anxiety and depression on the quality of life of hemodialysis patients. MATERIAL & METHODS: The sample studied consisted of 395 hemodialysis patients. Data was collected by the completion of a specially designed questionnaire for the needs of the present study which apart from socio-demographic and clinical, it also included HADS scale to assess the level of anxiety and depression as well as the scale Missoula-VITAS Quality of Life Index (MVQOLI) to assess patients' quality of life. RESULTS: The results of this study showed that 47.8% had high anxiety levels and 38.2% had high levels of depression. The average total score of quality of life was found to be 17.14. It was also shown that the total score of quality of life presented statistically significant association with family status (p=0.007), educational level (p<0.001), the number of children (p=0.001), patients' adherence to doctors' orders (p=0.003) and proposed diet (p=0.002) and the relations of patients with healthcare professionals and the other patients (p<0.001). The multiple linear regression showed that the overall quality of life score was statistically associated with the levels of depression after adjusted for possible confounders. More specifically, it was found that total score of quality of life was 2.5 and 4.4 points lower for patients with moderate and high levels of depression, respectively, compared to patients with low levels of depression (p<0.001). CONCLUSIONS: Evaluation of anxiety and depression in conjunction with quality of life in hemodialysis patients should be an integral part of the therapeutic regimen.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".